SpecP: A tool for spectral partitioning of protein contact graph
نویسندگان
چکیده
SpecP is an open-source Python module that performs Spectral Partitioning on Protein Contact Graphs. Protein Contact Graphs are graph theory based representation of the protein structure, where each amino acid forms a 'vertex' and spatial contact of any two amino acids is an 'edge' between them. Spectral partitioning is carried out in SpecP based on the second smallest spectral value (eigen value) of the Protein Contact Graph. The eigen vector corresponding to the second smallest spectral value are partitioned into two clusters based on the sign of the corresponding vector entry. Spectral Partitioning algorithm is repeatedly carried out until the desired numbers of partitions are obtained. SpecP visualizes the spectrally partitioned clusters of protein structure along with the Protein Contact Map and Protein Contact Graph which can be saved for later use. It also possesses an interactive mode whereby the user has the ability to zoom, pan, resize and save these raster images in various image formats (.eps, .jpg, .png) manually. SpecP is a stand-alone extensible tool useful for structural analysis of proteins.
منابع مشابه
A New Thermodynamic Approach for Protein Partitioning in Reverse Micellar Solution
Reverse micellar systems are nanofluids with unique properties that make them attractive in high selectivity separation processes, especially for biological compounds. Understanding the phase behavior and thermodynamic properties of these nanosystems is the first step in process design. Separation of components by these nanosystems is performed upon contact of aqueous and reverse micellar phase...
متن کاملSIGNLESS LAPLACIAN SPECTRAL MOMENTS OF GRAPHS AND ORDERING SOME GRAPHS WITH RESPECT TO THEM
Let $G = (V, E)$ be a simple graph. Denote by $D(G)$ the diagonal matrix $diag(d_1,cdots,d_n)$, where $d_i$ is the degree of vertex $i$ and $A(G)$ the adjacency matrix of $G$. The signless Laplacianmatrix of $G$ is $Q(G) = D(G) + A(G)$ and the $k-$th signless Laplacian spectral moment of graph $G$ is defined as $T_k(G)=sum_{i=1}^{n}q_i^{k}$, $kgeqslant 0$, where $q_1$,$q_2$, $cdots$, $q_n$ ...
متن کاملOn the Maximal Error of Spectral Approximation of Graph Bisection
Spectral graph bisections are a popular heuristic aimed at approximating the solution of the NP-complete graph bisection problem. This technique, however, does not always provide a robust tool for graph partitioning. Using a special class of graphs, we prove that the standard spectral graph bisection can produce bisections that are far from optimal. In particular, we show that the maximum error...
متن کاملGreen Functions on Self–Similar Graphs and Bounds for the Spectrum of the Laplacian
Combining the study of the simple random walk on graphs, generating functions (especially Green functions), complex dynamics and general complex analysis we introduce a new method of spectral analysis on self-similar graphs. We give an axiomatic definition of self-similar graphs which correspond to general nested but not necessarily finitely ramified fractals. For this class of graphs a graph t...
متن کاملNew Graph Partitioning Algorithms 1
Graph partitioning problems are NP-complete and various heuristic algorithms exist in the litterature. Particularly, spectral graph partitioning algorithms partition the graph using the eigenvector associated with the second smallest eigenvalue of the \graph Laplacian." Through the use of graph theory we have devoloped preconditioned subspace algorithms for spectral partitioning.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 9 شماره
صفحات -
تاریخ انتشار 2013